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<div class="mycontent">



<p><br><br><br>This document gives a few suggestions to analyse a
dataset composed by <code>three numeric variables</code>. It considers
an abstract of the <a
href="https://www.gapminder.org/data/">Gapminder</a> dataset made famous
through the <a
href="https://www.ted.com/talks/hans_rosling_shows_the_best_stats_you_ve_ever_seen">Hans
Rosling Ted Talk</a>. It provides the average life expectancy, gdp per
capita and population size for more than 100 countries. This dataset is
available through the <code>gapminder</code> R package and you can
download it <a
href="https://github.com/holtzy/data_to_viz/tree/master/Example_dataset">here</a>.
The table beside shows a glimpse of it.</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" tabindex="-1"></a><span class="co"># Libraries</span></span>
<span id="cb1-2"><a href="#cb1-2" tabindex="-1"></a><span class="fu">library</span>(tidyverse)</span>
<span id="cb1-3"><a href="#cb1-3" tabindex="-1"></a><span class="fu">library</span>(hrbrthemes)</span>
<span id="cb1-4"><a href="#cb1-4" tabindex="-1"></a><span class="fu">library</span>(viridis)</span>
<span id="cb1-5"><a href="#cb1-5" tabindex="-1"></a><span class="fu">library</span>(kableExtra)</span>
<span id="cb1-6"><a href="#cb1-6" tabindex="-1"></a><span class="fu">options</span>(<span class="at">knitr.table.format =</span> <span class="st">&quot;html&quot;</span>)</span>
<span id="cb1-7"><a href="#cb1-7" tabindex="-1"></a><span class="fu">library</span>(plotly)</span>
<span id="cb1-8"><a href="#cb1-8" tabindex="-1"></a><span class="fu">library</span>(gridExtra)</span>
<span id="cb1-9"><a href="#cb1-9" tabindex="-1"></a><span class="fu">library</span>(ggrepel)</span>
<span id="cb1-10"><a href="#cb1-10" tabindex="-1"></a></span>
<span id="cb1-11"><a href="#cb1-11" tabindex="-1"></a><span class="co"># The dataset is provided in the gapminder library</span></span>
<span id="cb1-12"><a href="#cb1-12" tabindex="-1"></a><span class="fu">library</span>(gapminder)</span>
<span id="cb1-13"><a href="#cb1-13" tabindex="-1"></a>data <span class="ot">&lt;-</span> gapminder <span class="sc">%&gt;%</span> <span class="fu">filter</span>(year<span class="sc">==</span><span class="st">&quot;2007&quot;</span>) <span class="sc">%&gt;%</span> <span class="fu">select</span>(<span class="sc">-</span>year)</span>
<span id="cb1-14"><a href="#cb1-14" tabindex="-1"></a></span>
<span id="cb1-15"><a href="#cb1-15" tabindex="-1"></a><span class="co"># show data</span></span>
<span id="cb1-16"><a href="#cb1-16" tabindex="-1"></a>data <span class="sc">%&gt;%</span> <span class="fu">head</span>(<span class="dv">6</span>) <span class="sc">%&gt;%</span></span>
<span id="cb1-17"><a href="#cb1-17" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">gdpPercap=</span><span class="fu">round</span>(gdpPercap,<span class="dv">0</span>)) <span class="sc">%&gt;%</span></span>
<span id="cb1-18"><a href="#cb1-18" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">pop=</span><span class="fu">round</span>(pop<span class="sc">/</span><span class="dv">1000000</span>,<span class="dv">2</span>)) <span class="sc">%&gt;%</span></span>
<span id="cb1-19"><a href="#cb1-19" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">lifeExp=</span><span class="fu">round</span>(lifeExp,<span class="dv">1</span>)) <span class="sc">%&gt;%</span></span>
<span id="cb1-20"><a href="#cb1-20" tabindex="-1"></a>  <span class="fu">kable</span>() <span class="sc">%&gt;%</span></span>
<span id="cb1-21"><a href="#cb1-21" tabindex="-1"></a>  <span class="fu">kable_styling</span>(<span class="at">bootstrap_options =</span> <span class="st">&quot;striped&quot;</span>, <span class="at">full_width =</span> F)</span></code></pre></div>
<table class="table table-striped" style="width: auto !important; margin-left: auto; margin-right: auto;">
<thead>
<tr>
<th style="text-align:left;">
country
</th>
<th style="text-align:left;">
continent
</th>
<th style="text-align:right;">
lifeExp
</th>
<th style="text-align:right;">
pop
</th>
<th style="text-align:right;">
gdpPercap
</th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align:left;">
Afghanistan
</td>
<td style="text-align:left;">
Asia
</td>
<td style="text-align:right;">
43.8
</td>
<td style="text-align:right;">
31.89
</td>
<td style="text-align:right;">
975
</td>
</tr>
<tr>
<td style="text-align:left;">
Albania
</td>
<td style="text-align:left;">
Europe
</td>
<td style="text-align:right;">
76.4
</td>
<td style="text-align:right;">
3.60
</td>
<td style="text-align:right;">
5937
</td>
</tr>
<tr>
<td style="text-align:left;">
Algeria
</td>
<td style="text-align:left;">
Africa
</td>
<td style="text-align:right;">
72.3
</td>
<td style="text-align:right;">
33.33
</td>
<td style="text-align:right;">
6223
</td>
</tr>
<tr>
<td style="text-align:left;">
Angola
</td>
<td style="text-align:left;">
Africa
</td>
<td style="text-align:right;">
42.7
</td>
<td style="text-align:right;">
12.42
</td>
<td style="text-align:right;">
4797
</td>
</tr>
<tr>
<td style="text-align:left;">
Argentina
</td>
<td style="text-align:left;">
Americas
</td>
<td style="text-align:right;">
75.3
</td>
<td style="text-align:right;">
40.30
</td>
<td style="text-align:right;">
12779
</td>
</tr>
<tr>
<td style="text-align:left;">
Australia
</td>
<td style="text-align:left;">
Oceania
</td>
<td style="text-align:right;">
81.2
</td>
<td style="text-align:right;">
20.43
</td>
<td style="text-align:right;">
34435
</td>
</tr>
</tbody>
</table>
<div id="bubble-plot" class="section level1">
<h1>Bubble plot</h1>
<hr />
<p>The go to graph in that kind of situation is probably the <a
href="">bubble plot</a>. The bubble plot is really close to a <a
href="">scatterplot</a> since it shows the value of two numeric
variables on the X and Y axis. However, it allows to study the value of
a third variable using different sizes for the dots (that are thus
called bubbles).</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" tabindex="-1"></a><span class="co"># Show a bubbleplot</span></span>
<span id="cb2-2"><a href="#cb2-2" tabindex="-1"></a>data <span class="sc">%&gt;%</span></span>
<span id="cb2-3"><a href="#cb2-3" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">pop=</span>pop<span class="sc">/</span><span class="dv">1000000</span>) <span class="sc">%&gt;%</span></span>
<span id="cb2-4"><a href="#cb2-4" tabindex="-1"></a>  <span class="fu">arrange</span>(<span class="fu">desc</span>(pop)) <span class="sc">%&gt;%</span></span>
<span id="cb2-5"><a href="#cb2-5" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">country =</span> <span class="fu">factor</span>(country, country)) <span class="sc">%&gt;%</span></span>
<span id="cb2-6"><a href="#cb2-6" tabindex="-1"></a>  <span class="fu">ggplot</span>( <span class="fu">aes</span>(<span class="at">x=</span>gdpPercap, <span class="at">y=</span>lifeExp, <span class="at">size =</span> pop, <span class="at">color =</span> continent)) <span class="sc">+</span></span>
<span id="cb2-7"><a href="#cb2-7" tabindex="-1"></a>    <span class="fu">geom_point</span>(<span class="at">alpha=</span><span class="fl">0.7</span>) <span class="sc">+</span></span>
<span id="cb2-8"><a href="#cb2-8" tabindex="-1"></a>    <span class="fu">scale_size</span>(<span class="at">range =</span> <span class="fu">c</span>(<span class="fl">1.4</span>, <span class="dv">19</span>), <span class="at">name=</span><span class="st">&quot;Population (M)&quot;</span>) <span class="sc">+</span></span>
<span id="cb2-9"><a href="#cb2-9" tabindex="-1"></a>    <span class="fu">scale_color_viridis</span>(<span class="at">discrete=</span><span class="cn">TRUE</span>, <span class="at">guide=</span><span class="cn">FALSE</span>) <span class="sc">+</span></span>
<span id="cb2-10"><a href="#cb2-10" tabindex="-1"></a>    <span class="fu">theme_ipsum</span>() <span class="sc">+</span></span>
<span id="cb2-11"><a href="#cb2-11" tabindex="-1"></a>    <span class="fu">theme</span>(<span class="at">legend.position=</span><span class="st">&quot;bottom&quot;</span>)</span></code></pre></div>
<p><img src="ThreeNum_files/figure-html/unnamed-chunk-2-1.png" width="960" style="display: block; margin: auto;" /></p>
<p>The problem with bubble plot is that the relationship between the
variable of the X and Y axis is much more obvious than the relationship
with the third variable. Thus you must prioritize your variables and be
sure of what you want to show. Before doing that kind of chart, I
believe it is a good practice to try other combinations:</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb3-1"><a href="#cb3-1" tabindex="-1"></a>p2 <span class="ot">&lt;-</span> data <span class="sc">%&gt;%</span></span>
<span id="cb3-2"><a href="#cb3-2" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">pop=</span>pop<span class="sc">/</span><span class="dv">1000000</span>) <span class="sc">%&gt;%</span></span>
<span id="cb3-3"><a href="#cb3-3" tabindex="-1"></a>  <span class="fu">arrange</span>(<span class="fu">desc</span>(pop)) <span class="sc">%&gt;%</span></span>
<span id="cb3-4"><a href="#cb3-4" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">country =</span> <span class="fu">factor</span>(country, country)) <span class="sc">%&gt;%</span></span>
<span id="cb3-5"><a href="#cb3-5" tabindex="-1"></a>  <span class="fu">ggplot</span>( <span class="fu">aes</span>(<span class="at">x=</span>gdpPercap, <span class="at">y=</span>pop, <span class="at">size =</span> lifeExp, <span class="at">color =</span> continent)) <span class="sc">+</span></span>
<span id="cb3-6"><a href="#cb3-6" tabindex="-1"></a>    <span class="fu">geom_point</span>(<span class="at">alpha=</span><span class="fl">0.7</span>) <span class="sc">+</span></span>
<span id="cb3-7"><a href="#cb3-7" tabindex="-1"></a>    <span class="fu">scale_color_viridis</span>(<span class="at">discrete=</span><span class="cn">TRUE</span>) <span class="sc">+</span></span>
<span id="cb3-8"><a href="#cb3-8" tabindex="-1"></a>    <span class="fu">scale_y_log10</span>() <span class="sc">+</span></span>
<span id="cb3-9"><a href="#cb3-9" tabindex="-1"></a>    <span class="fu">theme_ipsum</span>() <span class="sc">+</span></span>
<span id="cb3-10"><a href="#cb3-10" tabindex="-1"></a>    <span class="fu">theme</span>(<span class="at">legend.position=</span><span class="st">&quot;none&quot;</span>)</span>
<span id="cb3-11"><a href="#cb3-11" tabindex="-1"></a></span>
<span id="cb3-12"><a href="#cb3-12" tabindex="-1"></a>p3 <span class="ot">&lt;-</span> data <span class="sc">%&gt;%</span></span>
<span id="cb3-13"><a href="#cb3-13" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">pop=</span>pop<span class="sc">/</span><span class="dv">1000000</span>) <span class="sc">%&gt;%</span></span>
<span id="cb3-14"><a href="#cb3-14" tabindex="-1"></a>  <span class="fu">arrange</span>(<span class="fu">desc</span>(pop)) <span class="sc">%&gt;%</span></span>
<span id="cb3-15"><a href="#cb3-15" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">country =</span> <span class="fu">factor</span>(country, country)) <span class="sc">%&gt;%</span></span>
<span id="cb3-16"><a href="#cb3-16" tabindex="-1"></a>  <span class="fu">ggplot</span>( <span class="fu">aes</span>(<span class="at">x=</span>lifeExp, <span class="at">y=</span>pop, <span class="at">size =</span> gdpPercap, <span class="at">color =</span> continent)) <span class="sc">+</span></span>
<span id="cb3-17"><a href="#cb3-17" tabindex="-1"></a>    <span class="fu">geom_point</span>(<span class="at">alpha=</span><span class="fl">0.7</span>) <span class="sc">+</span></span>
<span id="cb3-18"><a href="#cb3-18" tabindex="-1"></a>    <span class="fu">scale_color_viridis</span>(<span class="at">discrete=</span><span class="cn">TRUE</span>) <span class="sc">+</span></span>
<span id="cb3-19"><a href="#cb3-19" tabindex="-1"></a>    <span class="fu">scale_y_log10</span>() <span class="sc">+</span></span>
<span id="cb3-20"><a href="#cb3-20" tabindex="-1"></a>    <span class="fu">theme_ipsum</span>() <span class="sc">+</span></span>
<span id="cb3-21"><a href="#cb3-21" tabindex="-1"></a>    <span class="fu">theme</span>(<span class="at">legend.position=</span><span class="st">&quot;none&quot;</span>)</span>
<span id="cb3-22"><a href="#cb3-22" tabindex="-1"></a></span>
<span id="cb3-23"><a href="#cb3-23" tabindex="-1"></a></span>
<span id="cb3-24"><a href="#cb3-24" tabindex="-1"></a><span class="fu">grid.arrange</span>(p2,p3, <span class="at">ncol=</span><span class="dv">2</span>)</span></code></pre></div>
<p><img src="ThreeNum_files/figure-html/unnamed-chunk-3-1.png" width="960" style="display: block; margin: auto;" /></p>
<p>In this case there is no obvious relationship between opulation and
other metrics so it makes sense to use population for the bubble
size.</p>
<p>If you just want to highlight the relationship between gbp per capita
and life Expectancy you’ve probably done most of the work now. However,
it is a good practice to highlight a few interesting dots in this chart
to give more insight to the plot:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb4-1"><a href="#cb4-1" tabindex="-1"></a><span class="co"># Prepare data</span></span>
<span id="cb4-2"><a href="#cb4-2" tabindex="-1"></a>tmp <span class="ot">&lt;-</span> data <span class="sc">%&gt;%</span></span>
<span id="cb4-3"><a href="#cb4-3" tabindex="-1"></a> <span class="fu">mutate</span>(</span>
<span id="cb4-4"><a href="#cb4-4" tabindex="-1"></a>   <span class="at">annotation =</span> <span class="fu">case_when</span>(</span>
<span id="cb4-5"><a href="#cb4-5" tabindex="-1"></a>    gdpPercap <span class="sc">&gt;</span> <span class="dv">5000</span> <span class="sc">&amp;</span> lifeExp <span class="sc">&lt;</span> <span class="dv">60</span> <span class="sc">~</span> <span class="st">&quot;yes&quot;</span>,</span>
<span id="cb4-6"><a href="#cb4-6" tabindex="-1"></a>    lifeExp <span class="sc">&lt;</span> <span class="dv">30</span> <span class="sc">~</span> <span class="st">&quot;yes&quot;</span>,</span>
<span id="cb4-7"><a href="#cb4-7" tabindex="-1"></a>     gdpPercap <span class="sc">&gt;</span> <span class="dv">40000</span> <span class="sc">~</span> <span class="st">&quot;yes&quot;</span></span>
<span id="cb4-8"><a href="#cb4-8" tabindex="-1"></a>    )</span>
<span id="cb4-9"><a href="#cb4-9" tabindex="-1"></a>) <span class="sc">%&gt;%</span></span>
<span id="cb4-10"><a href="#cb4-10" tabindex="-1"></a><span class="fu">mutate</span>(<span class="at">pop=</span>pop<span class="sc">/</span><span class="dv">1000000</span>) <span class="sc">%&gt;%</span></span>
<span id="cb4-11"><a href="#cb4-11" tabindex="-1"></a>  <span class="fu">arrange</span>(<span class="fu">desc</span>(pop)) <span class="sc">%&gt;%</span></span>
<span id="cb4-12"><a href="#cb4-12" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">country =</span> <span class="fu">factor</span>(country, country))</span>
<span id="cb4-13"><a href="#cb4-13" tabindex="-1"></a></span>
<span id="cb4-14"><a href="#cb4-14" tabindex="-1"></a><span class="co"># Plot</span></span>
<span id="cb4-15"><a href="#cb4-15" tabindex="-1"></a><span class="fu">ggplot</span>( tmp, <span class="fu">aes</span>(<span class="at">x=</span>gdpPercap, <span class="at">y=</span>lifeExp, <span class="at">size =</span> pop, <span class="at">color =</span> continent)) <span class="sc">+</span></span>
<span id="cb4-16"><a href="#cb4-16" tabindex="-1"></a>    <span class="fu">geom_point</span>(<span class="at">alpha=</span><span class="fl">0.7</span>) <span class="sc">+</span></span>
<span id="cb4-17"><a href="#cb4-17" tabindex="-1"></a>    <span class="fu">scale_size</span>(<span class="at">range =</span> <span class="fu">c</span>(<span class="fl">1.4</span>, <span class="dv">19</span>), <span class="at">name=</span><span class="st">&quot;Population (M)&quot;</span>) <span class="sc">+</span></span>
<span id="cb4-18"><a href="#cb4-18" tabindex="-1"></a>    <span class="fu">scale_color_viridis</span>(<span class="at">discrete=</span><span class="cn">TRUE</span>) <span class="sc">+</span></span>
<span id="cb4-19"><a href="#cb4-19" tabindex="-1"></a>    <span class="fu">theme_ipsum</span>() <span class="sc">+</span></span>
<span id="cb4-20"><a href="#cb4-20" tabindex="-1"></a>    <span class="fu">theme</span>(<span class="at">legend.position=</span><span class="st">&quot;none&quot;</span>) <span class="sc">+</span></span>
<span id="cb4-21"><a href="#cb4-21" tabindex="-1"></a>    <span class="fu">geom_text_repel</span>(<span class="at">data=</span>tmp <span class="sc">%&gt;%</span> <span class="fu">filter</span>(annotation<span class="sc">==</span><span class="st">&quot;yes&quot;</span>), <span class="fu">aes</span>(<span class="at">label=</span>country), <span class="at">size=</span><span class="dv">4</span> )</span></code></pre></div>
<p><img src="ThreeNum_files/figure-html/unnamed-chunk-4-1.png" width="960" style="display: block; margin: auto;" /></p>
<p>Last but not least, note that bubble plot is probably the type of
chart where using interactivity makes the more sense. In the following
plot you can hover bubbles to get more information and zoom on a
specific part of the graphic.</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb5-1"><a href="#cb5-1" tabindex="-1"></a><span class="co"># Interactive version</span></span>
<span id="cb5-2"><a href="#cb5-2" tabindex="-1"></a>p <span class="ot">&lt;-</span> data <span class="sc">%&gt;%</span></span>
<span id="cb5-3"><a href="#cb5-3" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">gdpPercap=</span><span class="fu">round</span>(gdpPercap,<span class="dv">0</span>)) <span class="sc">%&gt;%</span></span>
<span id="cb5-4"><a href="#cb5-4" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">pop=</span><span class="fu">round</span>(pop<span class="sc">/</span><span class="dv">1000000</span>,<span class="dv">2</span>)) <span class="sc">%&gt;%</span></span>
<span id="cb5-5"><a href="#cb5-5" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">lifeExp=</span><span class="fu">round</span>(lifeExp,<span class="dv">1</span>)) <span class="sc">%&gt;%</span></span>
<span id="cb5-6"><a href="#cb5-6" tabindex="-1"></a>  <span class="fu">arrange</span>(<span class="fu">desc</span>(pop)) <span class="sc">%&gt;%</span></span>
<span id="cb5-7"><a href="#cb5-7" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">country =</span> <span class="fu">factor</span>(country, country)) <span class="sc">%&gt;%</span></span>
<span id="cb5-8"><a href="#cb5-8" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">text =</span> <span class="fu">paste</span>(<span class="st">&quot;Country: &quot;</span>, country, <span class="st">&quot;</span><span class="sc">\n</span><span class="st">Population (M): &quot;</span>, pop, <span class="st">&quot;</span><span class="sc">\n</span><span class="st">Life Expectancy: &quot;</span>, lifeExp, <span class="st">&quot;</span><span class="sc">\n</span><span class="st">Gdp per capita: &quot;</span>, gdpPercap, <span class="at">sep=</span><span class="st">&quot;&quot;</span>)) <span class="sc">%&gt;%</span></span>
<span id="cb5-9"><a href="#cb5-9" tabindex="-1"></a>  <span class="fu">ggplot</span>( <span class="fu">aes</span>(<span class="at">x=</span>gdpPercap, <span class="at">y=</span>lifeExp, <span class="at">size =</span> pop, <span class="at">color =</span> continent, <span class="at">text=</span>text)) <span class="sc">+</span></span>
<span id="cb5-10"><a href="#cb5-10" tabindex="-1"></a>    <span class="fu">geom_point</span>(<span class="at">alpha=</span><span class="fl">0.7</span>) <span class="sc">+</span></span>
<span id="cb5-11"><a href="#cb5-11" tabindex="-1"></a>    <span class="fu">scale_size</span>(<span class="at">range =</span> <span class="fu">c</span>(<span class="fl">1.4</span>, <span class="dv">19</span>), <span class="at">name=</span><span class="st">&quot;Population (M)&quot;</span>) <span class="sc">+</span></span>
<span id="cb5-12"><a href="#cb5-12" tabindex="-1"></a>    <span class="fu">scale_color_viridis</span>(<span class="at">discrete=</span><span class="cn">TRUE</span>, <span class="at">guide=</span><span class="cn">FALSE</span>) <span class="sc">+</span></span>
<span id="cb5-13"><a href="#cb5-13" tabindex="-1"></a>    <span class="fu">theme_ipsum</span>() <span class="sc">+</span></span>
<span id="cb5-14"><a href="#cb5-14" tabindex="-1"></a>    <span class="fu">theme</span>(<span class="at">legend.position=</span><span class="st">&quot;none&quot;</span>)</span>
<span id="cb5-15"><a href="#cb5-15" tabindex="-1"></a></span>
<span id="cb5-16"><a href="#cb5-16" tabindex="-1"></a><span class="fu">ggplotly</span>(p, <span class="at">tooltip=</span><span class="st">&quot;text&quot;</span>)</span></code></pre></div>
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</div>
<div id="a-note-on-the-grid-scenario" class="section level1">
<h1>A note on the grid scenario</h1>
<hr />
<div class="row">
<div class="col-md-8">
<p><br><br><br> A specific use case where three numeric columns are
displayed is the grid system. In this case, the two first columns gives
the grid coordinates, and the third variable gives a numeric value for
each position of the grid. For example, the volcano data set provides
that altitude of each point of the grid of a volcano:</p>
</div>
<div class="col-md-4">
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb6-1"><a href="#cb6-1" tabindex="-1"></a><span class="co"># prepare the dataset:</span></span>
<span id="cb6-2"><a href="#cb6-2" tabindex="-1"></a>don <span class="ot">&lt;-</span> volcano</span>
<span id="cb6-3"><a href="#cb6-3" tabindex="-1"></a><span class="fu">colnames</span>(don) <span class="ot">&lt;-</span> <span class="fu">seq</span>(<span class="dv">1</span>,<span class="fu">ncol</span>(don))</span>
<span id="cb6-4"><a href="#cb6-4" tabindex="-1"></a>don <span class="ot">&lt;-</span> don <span class="sc">%&gt;%</span></span>
<span id="cb6-5"><a href="#cb6-5" tabindex="-1"></a>  <span class="fu">as.tibble</span>() <span class="sc">%&gt;%</span></span>
<span id="cb6-6"><a href="#cb6-6" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">lat=</span><span class="fu">seq</span>(<span class="dv">1</span>,<span class="fu">nrow</span>(don)) ) <span class="sc">%&gt;%</span></span>
<span id="cb6-7"><a href="#cb6-7" tabindex="-1"></a>  <span class="fu">gather</span>(<span class="at">key=</span><span class="st">&quot;long&quot;</span>, <span class="at">value=</span><span class="st">&quot;altitude&quot;</span>, <span class="sc">-</span>lat)</span>
<span id="cb6-8"><a href="#cb6-8" tabindex="-1"></a></span>
<span id="cb6-9"><a href="#cb6-9" tabindex="-1"></a><span class="co"># show data</span></span>
<span id="cb6-10"><a href="#cb6-10" tabindex="-1"></a>don <span class="sc">%&gt;%</span> <span class="fu">head</span>(<span class="dv">6</span>) <span class="sc">%&gt;%</span> <span class="fu">kable</span>() <span class="sc">%&gt;%</span></span>
<span id="cb6-11"><a href="#cb6-11" tabindex="-1"></a>  <span class="fu">kable_styling</span>(<span class="at">bootstrap_options =</span> <span class="st">&quot;striped&quot;</span>, <span class="at">full_width =</span> F)</span></code></pre></div>
<table class="table table-striped" style="width: auto !important; margin-left: auto; margin-right: auto;">
<thead>
<tr>
<th style="text-align:right;">
lat
</th>
<th style="text-align:left;">
long
</th>
<th style="text-align:right;">
altitude
</th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align:right;">
1
</td>
<td style="text-align:left;">
1
</td>
<td style="text-align:right;">
100
</td>
</tr>
<tr>
<td style="text-align:right;">
2
</td>
<td style="text-align:left;">
1
</td>
<td style="text-align:right;">
101
</td>
</tr>
<tr>
<td style="text-align:right;">
3
</td>
<td style="text-align:left;">
1
</td>
<td style="text-align:right;">
102
</td>
</tr>
<tr>
<td style="text-align:right;">
4
</td>
<td style="text-align:left;">
1
</td>
<td style="text-align:right;">
103
</td>
</tr>
<tr>
<td style="text-align:right;">
5
</td>
<td style="text-align:left;">
1
</td>
<td style="text-align:right;">
104
</td>
</tr>
<tr>
<td style="text-align:right;">
6
</td>
<td style="text-align:left;">
1
</td>
<td style="text-align:right;">
105
</td>
</tr>
</tbody>
</table>
</div>
</div>
<p>This kind of data can be represented using a <a href="">heatmap</a>
(2d):</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb7-1"><a href="#cb7-1" tabindex="-1"></a>don <span class="sc">%&gt;%</span></span>
<span id="cb7-2"><a href="#cb7-2" tabindex="-1"></a>  <span class="fu">na.omit</span>() <span class="sc">%&gt;%</span></span>
<span id="cb7-3"><a href="#cb7-3" tabindex="-1"></a>  <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x=</span><span class="fu">as.numeric</span>(long), <span class="at">y=</span>lat, <span class="at">fill=</span>altitude)) <span class="sc">+</span></span>
<span id="cb7-4"><a href="#cb7-4" tabindex="-1"></a>    <span class="fu">geom_tile</span>() <span class="sc">+</span></span>
<span id="cb7-5"><a href="#cb7-5" tabindex="-1"></a>    <span class="fu">scale_fill_viridis</span>() <span class="sc">+</span></span>
<span id="cb7-6"><a href="#cb7-6" tabindex="-1"></a>    <span class="fu">theme_ipsum</span>() <span class="sc">+</span></span>
<span id="cb7-7"><a href="#cb7-7" tabindex="-1"></a>    <span class="fu">xlab</span>(<span class="st">&quot;longitude&quot;</span>) <span class="sc">+</span></span>
<span id="cb7-8"><a href="#cb7-8" tabindex="-1"></a>    <span class="fu">ylab</span>(<span class="st">&quot;latitude&quot;</span>)</span></code></pre></div>
<p><img src="ThreeNum_files/figure-html/unnamed-chunk-7-1.png" width="672" style="display: block; margin: auto;" /></p>
<p>Another way is to build a surface plot. It really makes sense to use
3D in this special case since it allows to visualize the real shape of
the volcano:</p>
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb8-1"><a href="#cb8-1" tabindex="-1"></a><span class="fu">plot_ly</span>(<span class="at">z =</span> volcano, <span class="at">type =</span> <span class="st">&quot;surface&quot;</span>)</span></code></pre></div>
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,127,126,125,124,122,121,119,118,117,116,114,113,112,110,109,108,106,106,105,100,100,100,98,98,98,98,98,98,97,97,97,97,97,97,97,96],[109,111,112,112,113,113,113,114,116,119,121,123,124,125,124,123,123,123,125,127,129,129,128,128,127,125,124,123,122,121,119,118,117,116,114,113,112,110,109,108,107,106,105,100,100,100,97,97,97,97,97,97,97,96,96,96,96,96,96,96,96],[106,107,108,108,109,110,110,112,113,114,117,119,120,121,119,117,117,117,118,120,123,124,125,125,125,123,121,120,120,119,118,117,116,115,114,113,111,109,109,107,106,105,100,100,100,96,96,96,96,96,96,96,96,96,96,96,96,96,96,96,96],[104,105,105,106,106,107,108,108,109,109,111,115,116,114,113,112,111,110,111,113,116,119,122,122,122,121,120,119,118,118,117,116,115,114,113,112,111,108,108,106,105,100,100,100,96,96,96,96,96,96,96,96,96,96,96,96,96,96,96,96,96],[102,103,103,104,104,105,106,106,107,108,109,111,112,110,109,108,108,108,108,109,110,112,116,117,117,118,118,118,117,116,116,115,114,113,112,111,110,107,107,105,100,100,100,97,96,96,96,96,96,96,96,96,96,96,96,96,96,96,96,96,96],[101,102,103,103,104,105,105,106,106,107,108,109,109,107,106,106,105,105,105,106,107,108,109,110,111,113,114,115,115,115,114,113,112,111,110,108,108,106,105,100,100,100,97,97,96,96,96,96,96,96,96,96,96,96,96,96,96,96,96,96,96],[100,101,102,102,103,103,104,104,105,106,106,107,106,106,106,105,105,104,103,103,104,105,107,108,110,111,111,112,112,113,113,112,111,110,108,107,106,105,100,100,100,98,97,97,96,96,96,96,96,96,96,96,96,96,96,96,96,96,96,96,96],[100,101,101,102,102,103,103,104,104,105,105,105,105,106,105,105,104,103,102,101,102,103,104,106,107,110,111,111,111,112,112,112,110,107,107,106,105,102,100,100,99,98,97,97,96,96,96,96,96,96,96,96,96,96,96,96,96,96,96,96,95],[99,100,101,102,102,103,103,103,104,104,104,104,103,104,104,104,104,102,101,101,102,103,104,105,107,110,111,111,111,111,111,111,108,106,105,105,102,101,100,99,99,98,97,97,96,96,96,96,96,96,96,96,96,96,96,96,96,96,96,95,95],[99,100,100,101,101,102,102,102,103,103,103,103,102,103,103,104,103,102,101,101,101,102,103,104,106,109,110,111,111,111,110,110,107,105,103,104,100,100,99,99,98,98,97,97,96,96,96,96,96,96,96,96,96,96,95,95,95,95,95,95,95],[99,100,100,100,101,101,101,102,102,103,102,102,101,102,102,103,103,101,101,100,101,101,102,103,105,109,110,110,111,110,110,109,106,105,100,102,100,99,99,99,98,98,97,97,96,96,96,96,96,96,95,95,95,95,95,95,95,95,95,95,94],[99,99,99,99,100,100,101,101,102,102,101,101,101,101,101,102,102,101,100,100,101,101,101,103,104,107,109,109,110,110,109,108,105,102,100,100,99,99,99,98,98,98,97,96,96,96,96,96,95,95,95,95,95,95,95,94,94,94,94,94,94],[98,99,99,99,99,100,100,101,101,102,101,100,100,100,101,101,101,100,100,100,100,101,101,101,103,106,107,109,109,109,109,107,104,101,100,99,99,99,98,98,98,97,96,96,96,96,95,95,95,95,95,95,95,94,94,94,94,94,94,94,94],[98,98,98,99,99,99,100,100,101,101,100,100,99,99,100,100,100,100,100,100,100,101,101,101,102,105,106,109,108,109,107,105,102,100,100,99,99,98,98,98,97,96,96,96,96,95,95,95,95,95,95,94,94,94,94,94,94,94,94,94,94],[97,98,98,98,99,99,99,100,100,100,100,100,99,99,99,100,100,100,100,100,100,100,101,101,101,103,104,105,106,105,104,101,100,100,99,99,98,98,97,97,97,96,96,96,95,95,95,95,95,94,94,94,94,94,94,94,94,94,94,94,94],[97,97,97,98,98,99,99,99,100,100,100,99,99,99,99,99,100,100,100,100,100,100,101,101,100,100,100,100,100,100,100,100,100,100,99,99,98,97,97,97,96,96,96,95,95,95,95,94,94,94,94,94,94,94,94,94,94,94,94,94,94]],"type":"surface","frame":null}],"highlight":{"on":"plotly_click","persistent":false,"dynamic":false,"selectize":false,"opacityDim":0.20000000000000001,"selected":{"opacity":1},"debounce":0},"shinyEvents":["plotly_hover","plotly_click","plotly_selected","plotly_relayout","plotly_brushed","plotly_brushing","plotly_clickannotation","plotly_doubleclick","plotly_deselect","plotly_afterplot","plotly_sunburstclick"],"base_url":"https://plot.ly"},"evals":[],"jsHooks":[]}</script>
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          <h1>Going further</h1>
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            Dataviz decision tree
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     &nbsp;
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<p style="text-align: center;">A work by <a href="https://github.com/holtzy/">Yan Holtz</a> for <a href="https://data-to-viz.com">data-to-viz.com</a></p>

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